MICROCHIP MPF200T-FCG784 PolarFire Ethernet Sensor Bridge

Introduction

The PolarFire® Ethernet Sensor Bridge is part of Nvidia’s Holoscan Ecosystem and extends multi-protocol signal conversion to NVIDIA® Jetsonâ„¢ Orinâ„¢ AGX and IGX developer kits via Ethernet.
The sensor bridge is based on Microchip’s power-efficient PolarFire Field-Programmable Gate Array (FPGA), MPF200T-FCG784. It has two 10G SFP+ Ethernet ports that connect to the Jetson AGX Orin and IGX developer kits and two MIPI CSI-2 receive ports for connecting cameras. The included FMC slot provides expansion options for protocols like Scalable Low-Voltage Signaling with Embedded Clock (SLVS-EC), CoaXPress, JESD 204B, Serial Digital Interface (SDI), and so on. The sensor bridge also has DDR4 for frame buffering and SPI Flash for enabling field upgrades.

The following table lists the Ethernet Sensor Bridge (ESB) kit contents.

Table 1. Kit Contents

The following figure shows the PolarFire ESB Kit contents.

Hardware Features

The following figure shows the board components.

Demo Requirements

Table 2-1. Pre-requisites for the Demo

Note: The Quick Start Guide provides setup instructions for use with a Jetson Orin AGX Developer Kit. If you are using an IGX Developer Kit, follow the specific steps intended for the IGX kit. We highlight the sections where instructions differ for each kit.

Running the Demo

The scope of this quick start guide is to get you set up and run a single MIPI CSI-2 camera streaming video via 10G Ethernet to the NVIDIA Jetson AGX Orin Developer Kit, which connects to a monitor via DisplayPort.
The PolarFire ESB is pre-programmed to support two IMX477 MIPI CSI-2 cameras from Arducam. However, only one Camera module is provided in the box.
The following figure shows the functional block diagram.

Figure 3-1. Functional Block Diagram

Setting up the Demonstration
The following table list the setup summary.

Setting up the PolarFire ESB
The following table lists the jumpers and their default position, ensure that the jumpers in the ESB are set correctly.

Table 3-1. Jumper setting for ESB

Camera Setup
To set up the camera, perform the following steps:

1. Make sure the MPF200-ETH-SENSOR-BRIDGE board is powered OFF.
2. Connect the IMX477 Camera module to J14 MIPI connector using the 22-pin to 22-pin camera cable, as shown in the following figure.
3. Insert SFP+ to RJ45 converter into the SFP cage on J5.
4. Connect the Ethernet cable from the SFP+ RJ45 port to the Ethernet port on NVIDIA Jetson AGX Orin Developer Kit, as shown in the following figure.
5. Connect the 12V power adapter to the J25 power input port.
6. To turn on the board, slide the switch SW1 to the ON position.

Setting up the AGX Orin developer kit

1. Run the steps in the Getting Started with Jetson AGX Orin Developer Kit.
2. While on the getting started page, choose the “Default setup flow” instead of the “Optional Setup Flow” and when scrolling down, choose “Initial setup with display attached” instead of the “Initial setup in a headless configuration”.
   Note: This step can take a long time. Make sure you have a stable internet connection.

Jetson AGX Orin Developer Kit Setup Host Setup
The PolarFire sensor bridge is supported on AGX Orin systems running JP6.0 release 2. In this configuration, the on-board Ethernet controller is used with the Linux kernel network stack for data I/O; all network I/O is performed by the CPU without network acceleration.

After the PolarFire Ethernet Sensor Bridge board is set up, configure a few prerequisites in your host system. While sensor bridge applications run in a container, these commands are all to be executed outside the container, on the host system directly. These configurations are remembered across power cycles and therefore only need to be set up once.

1. Install git-lfs.
   Some data files in the sensor bridge source repository use GIT LFS.
   sudo apt-get update
   sudo apt-get install -y git-lfs
2. Grant your user permission to the docker subsystem:
   $ sudo usermod -aG docker $USER
   Reboot the computer to activate this setting.
   Demos and examples in this package assume a sensor bridge device is connected to eth0, which is the RJ45 connector on the AGX Orin.
3. Linux sockets require a larger network receiver buffer.
   Most sensor bridge self-tests use Linux’s loopback interface; if the kernel starts dropping packets due to out-of-buffer space then these tests will fail.
   echo ‘net.core.rmem_max = 31326208’ | sudo tee /etc/sysctl.d/52-hololink-rmem_max.conf
   sudo sysctl -p /etc/sysctl.d/52-hololink-rmem_max.conf
4. Configure eth0 for a static IP address of 192.168.0.101.
   L4T uses NetworkManager to configure interfaces; by default, interfaces are configured as DHCP clients. Use the following command to update the IP address to 192.168.0.101. For more information about configuring your system, see Holoscan sensor bridge IP address configuration (If you cannot use the 192.168.0.0/24 network in this way).
   sudo nmcli con add con-name hololink-eth0 ifname eth0 type ethernet ip4 192.168.0.101/24
   sudo nmcli connection up hololink-eth0
   Apply power to the sensor bridge device, ensure that it’s properly connected, then ping 192.168.0.2 to check connectivity.
5. For the Linux socket-based examples, isolating a processor core from Linux kernel is recommended. For high bandwidth applications, like 4k video acquisition, isolation of the network receiver core is required. When an example program runs with processor affinity set to that isolated core, performance is improved, and latency is reduced. By default, sensor bridge software runs the time-critical background network receiver process on the third processor core. If that core is isolated from Linux scheduling, no processes will be scheduled on that core without an explicit request from the user, and reliability and performance is greatly improved.
   Isolating that core from Linux can be achieved by editing /boot/extlinux/extlinux.conf.
   Add the setting isolcpus=2 to the end of the line that starts with APPEND. Your file should look like something like this:
   TIMEOUT 30
   DEFAULT primary
   MENU TITLE L4T boot options
   LABEL primary
   MENU LABEL primary kernel
   LINUX /boot/Image
   FDT /boot/dtb/kernel_tegra234-p3701-0000-p3737-0000.dtb
   INITRD /boot/initrd
   APPEND ${cbootargs} root=/dev/mmcblk0p1 rw rootwait …<other-settings>… isolcpus=2
   Sensor bridge applications can run the network receiver process on another core by setting the environment variable HOLOLINK_AFFINITY to the core it should run on. For example, to run on the first processor core,
   HOLOLINK_AFFINITY=0 python3 examples/linux_imx477_player.py
   Setting HOLOLINK_AFFINITY to blank will skip any core affinity settings in the sensor bridge code.
6. Run the “jetson_clocks” tool on startup, to set the core clocks to their maximum.
   JETSON_CLOCKS_SERVICE=/etc/systemd/system/jetson_clocks.service
   cat <<EOF | sudo tee $JETSON_CLOCKS_SERVICE >/dev/null
   [Unit] Description=Jetson Clocks Startup
   After=nvpmodel.service
   [Service] Type=oneshot
   ExecStart=/usr/bin/jetson_clocks
   [Install] WantedBy=multi-user.target
   EOF
   sudo chmod u+x $JETSON_CLOCKS_SERVICE
   sudo systemctl enable jetson_clocks.service
7. Set the AGX Orin power mode to ‘MAXN’ for optimal performance, as shown in the following figure. The setting can be changed via L4T power drop down setting found on the upper left corner of the screen:
8. Restart the AGX Orin. This allows core isolation and performance settings to take effect. If configuring for ‘MAXN’ performance doesn’t request that you reset the unit, then execute the reboot command manually:
9. Log in to Nvidia GPU Cloud (NGC) with your developer account:
   a. If you don’t have a developer account for NGC please register at NVIDIA.
   b. Create an API key for your account, thru API Key.
   c. Use your API key to log in to nvcr.io:

Build and Test the Sensor Bridge Demo Container
Holoscan sensor bridge host software includes instructions for building a demo container. This container is used to run all holoscan tests and examples.

Note: igpu is appropriate for systems running on a system with iGPU (e.g. AGX or IGX without a dGPU). This requires an OS installed with iGPU support (For example: for AGX: JetPack 6.0, and for IGX: IGX OS with iGPU configuration).

Run Tests in the Demo Container
To run the sensor bridge demonstration container, from a terminal in the GUI,

This brings you to a shell prompt inside the Holoscan sensor bridge demo container.
Note: iGPU configurations, when starting the demo container it will display the message “Failed to detect NVIDIA driver version”: this can be ignored.
Now you’re ready to run sensor bridge applications.

Sensor Bridge Software Loopback Tests
Sensor bridge host software includes a test fixture that runs in loopback mode, where no sensor bridge equipment is necessary. This test works by generating UDP messages and sending them over the Linux loopback interface.

In the shell in the demo container:

Note: The test fixture intentionally introduces errors into the software stack. If pytest indicates that all tests have passed, any error messages published by individual tests can be ignored.

Running Examples

Two examples are described in this section

1. Streaming camera video
2. Running a pose estimation demo

Streaming the Video on AGX Developer Kit
This demonstration shows the output of the IMX477 camera module on the monitor connected via displayport. To run the high-speed video player with IMX477 setup, perform the following steps:

1. Open a new terminal and navigate to the holoscan-sensor-bridge folder by using the following command.
   cd <PATH/TO/holoscan-sensor-bridge>
2. To run the sensor bridge demonstration container, from a terminal in the GUI
   Note: Ignore the step if the docker is running already xhost + sh docker/demo.sh
   It runs the holoscan-sensor-bridge docker container.
3. Set up the camera and run the high-speed video player (Holoviz) with live video using the following command:
   python examples/linux_imx477_player.py
4. To close the Holoviz application and exit the docker, exit

Running Pose Estimation on GPU
To run this example, perform the following steps:

1. Download the file mpf_an522_v2023v2_jb.zip from AN5522.
2. Copy the file linux_imx477_pose_estimation.py into the folder holoscan-sensorbridge/ examples
3. Open a new terminal and navigate to the holoscan-sensor-bridge folder by using the following command.
   cd <PATH/TO/holoscan-sensor-bridge>
4. The next step involves downloading ffmpeg and ultralytics packages to run the pose estimation demo from Running Holoscan Sensor Bridge examples – NVIDIA Docs. Rather than going to the link above, type the following in the console
   apt-get update && apt-get install -y ffmpeg
   pip3 install ultralytics onnx
   cd examples
   yolo export model=yolov8n-pose.pt format=onnx
   cd
   Note: This conversion step only needs to be executed once; the yolov8n-pose.onnx file contains the converted model and is all that’s needed for the demo to run. The installed components will be forgotten when the container is exited; those do not need to be present in future runs of the demo.
5. To run the sensor bridge demonstration container, from a terminal in the GUI,
   Note: Ignore the step if the docker is running already
   xhost +
   sh docker/demo.sh
6. To run the pose estimation demo,
   python examples/linux_imx477_pose_estimation.py
7. Close the Holoviz application and exit the docker to terminate the application

Documentation Resources
For more information on the PolarFire ESB, including schematics and user’s guides, see the MPF200-Eth-sensor-bridge.

Microchip FPGA Support

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Contact Technical Support Center through the website at www.microchip.com/support. Mention the FPGA Device Part number, select appropriate case category, and upload design files while creating a technical support case.
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Documents / Resources

MICROCHIP MPF200T-FCG784 PolarFire Ethernet Sensor Bridge [pdf] User Guide MPF200T-FCG784 PolarFire Ethernet Sensor Bridge, MPF200T-FCG784, PolarFire Ethernet Sensor Bridge, Ethernet Sensor Bridge, Sensor Bridge, Bridge

References

• User Manual